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OverviewThe book addresses the problem of a time-varying unconditional variance of return processes utilizing a spline function. The knots of the spline functions are estimated as free parameters within a joined estimation process together with the parameters of the mean, the conditional variance and the spline function. With the help of this method, the knots are placed in regions where the unconditional variance is not smooth. The results are tested within an extensive simulation study and an empirical study employing the S&P500 index. Full Product DetailsAuthor: Oliver OldPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer Gabler Edition: 1st ed. 2022 Weight: 0.344kg ISBN: 9783658386177ISBN 10: 3658386177 Pages: 237 Publication Date: 28 July 2022 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsIntroduction.- Financial time series.- Smoothing long term volatility.- 4 Free-knot spline-GARCH model.- Simulation study.- Empirical study.- Conclusion.ReviewsAuthor InformationThe dissertation was written at the Chair of Applied Statistics and Methods of Empirical Social Research at the Faculty of Economics and Business Administration of the FernUniversität in Hagen. From 2021 Oliver Old researched in the field of applied statistics, machine learning and data science at two EU-Horizon projects at the Department of Anesthesiology, Intensive Care and Pain Therapy at the University Hospital Frankfurt. Tab Content 6Author Website:Countries AvailableAll regions |